Multistep greedy algorithm identifies community structure in real-world and computer-generated networks

We have recently introduced a multistep extension of the greedy algorithm for modularity optimization. The extension is based on the idea that merging l pairs of communities (l>1) at each iteration prevents premature condensation into few large communities. Here, an empirical formula is presented for the choice of the step width l that generates partitions with (close to) optimal modularity for 17 real-world and 1100 computer-generated networks. Furthermore, an in-depth analysis of the communities of two real-world networks (the metabolic network of the bacterium E. coli and the graph of coappearing words in the titles of papers coauthored by Martin Karplus) provides evidence that the partition obtained by the multistep greedy algorithm is superior to the one generated by the original greedy algorithm not only with respect to modularity but also according to objective criteria. In other words, the multistep extension of the greedy algorithm reduces the danger of getting trapped in local optima of modularity and generates more reasonable partitions.Comment: 17 pages, 2 figure

Prospect theory and tax evasion: A reconsideration of the Yitzhaki puzzle [WP]

The standard expected utility model of tax evasion predicts that evasion is decreasing in the marginal tax rate (the Yitzhaki puzzle). The existing literature disagrees on whether prospect theory overturns the puzzle. We disentangle four distinct elements of prospect theory and find loss aversion and probability weighting to be redundant in respect of the puzzle. Prospect theory fails to reverse the puzzle for various classes of endogenous specification of the reference level. These classes include, as special cases, the most common specifications in the literature. New specifications of the reference level are needed, we conclude

Is the new cognitive neuroscience of social inequality equal? Deconstructing the current neurocognitive research on children’s attention

The relation between socioeconomic status (SES) and various outcomes, such as cognitive ability, behavior, social skills and health, has been studied for over half a century. The general consensus in interpreting the results as been that low SES is necessarily associated with cognitive and/or behavioral pathologies or deficits. Contrary to this deficit hypothesis new evidence suggests that the differences between low- and high-SES populations may be due to cognitive preferences associated with the social context where children develop. Much of this evidence has come from developmental neuroimaging studies on attention and executive control generally showing that despite differences between low- and high-SES children in neural correlates, there are no behavioral differences. Still, from within the new cognitive neuroscience of social inequality the observed differences are used to argue that low-SES children have neurocognitive impairments needing intervention/remediation. Other current research shows that low SES is associated with elevated levels of stress, and that elevated levels of stress or treatments with stress-related neuropeptides can alter certain aspects of attention. Thus, variations in attention across different SES backgrounds may be mediated by environmental stress. We review critically the connections among SES, stress and attention as well as a number of ethical, methodological and theoretical implications for health research. We argue that the deficit hypothesis is too limiting and that a comprehensive explanation of the association between SES and attention, and possibly cognition in general, requires a much broader explanatory framework grounded in both ecological and developmental theorizing that takes social context seriously

Cognitive Sciences and Child Poverty: Facts and Challenges

In the context of cognitive neuroscience, the study of poverty and social gradients is a very young area of research where a core consensus of basic results is quickly emerging. However, as any emerging scientific discipline, the approaches used are influenced by epistemological stances inherited from other disciplines, and potentially implicit ideological systems as well. Explicitly or inadvertently, such influences can lead this critically important new area of research to methodological and ethical foundational challenges and to issues that are in need of debate (e.g., poverty definition criteria, lack of specificity when considering child poverty in terms of how children experience different type of deprivations, or lack of critics regarding social exclusion in different countries). Debate on these issues goes beyond consensus on interventions aiming at attenuating the effects of poverty on children’s development. Without an analysis of the emerging issues, scientist may dangerously risk the tendency to simplify the complexity that characterizes both phenomena of development and social inequality. The aim of the present paper is to contribute to a debate on the implicit and explicit conceptual and methodological assumptions underlying the current neurocognitive research on social inequality

Hydrogen-Accreting Carbon-Oxygen White Dwarfs of Low Mass: Thermal and Chemical Behavior of Burning Shells

Numerical experiments have been performed to investigate the thermal behavior of a cooled down white dwarf of initial mass M_{\rm WD} = 0.516 M_{\sun} which accretes hydrogen-rich matter with Z = 0.02 at the rate $\dot{M}=10^{-8}$ \msun \yrm1, typical for a recurrent hydrogen shell flash regime. The evolution of the main physical quantities of a model during a pulse cycle is examined in detail. From selected models in the mass range $M_{\rm WD} = 0.52\div 0.68$ \msunend, we derive the borders in the $M_{\rm WD}$ - $\dot{M}$ plane of the steady state accretion regime when hydrogen is burned at a constant rate as rapidly as it is accreted. The physical properties during a hydrogen shell flash in white dwarfs accreting hydrogen-rich matter with metallicities Z = 0.001 and Z = 0.0001 are also studied. For a fixed accretion rate, a decrease in the metallicity of the accreted matter leads to an increase in the thickness of the hydrogen-rich layer at outburst and a decrease in the hydrogen-burning shell efficiency. In the $M_{\rm WD}$-$\dot{M}$ plane, the borders of the steady state accretion band are critically dependent on the metallicity of the accreted matter: on decreasing the metallicity, the band is shifted to lower accretion rates and its width in $\dot{M}$ is reduced.Comment: 31 pages and 10 Postscript figures; Accepted for publication on Ap

Airport Congestion Mitigation through Dynamic Control of Runway Configurations and of Arrival and Departure Service Rates under Stochastic Operating Conditions

The high levels of flight delays require the implementation of airport congestion mitigation tools. In this paper, we optimize the utilization of airport capacity at the tactical level in the face of operational uncertainty. We formulate an original Dynamic Programming model that selects jointly and dynamically runway configurations and the balance of arrival and departure service rates at a busy airport to minimize congestion costs, under stochastic queue dynamics and stochastic operating conditions. The control is exercised as a function of flight schedules, of arrival and departure queue lengths and of weather and wind conditions. We implement the model in a realistic setting at JFK Airport. The exact Dynamic Programming algorithm terminates within reasonable time frames. In addition, we implement an approximate one-step look-ahead algorithm that considerably accelerates the execution of the model and results in close-to-optimal policies. In combination, these solution algorithms enable the on-line implementation of the model using real-time information on flight schedules and meteorological conditions. The application of the model shows that the optimal policy is path-dependent, i.e., it depends on prior decisions and on the stochastic evolution of arrival and departure queues during the day. This underscores the theoretical and practical need for integrating operating stochasticity into the decision-making framework. From comparisons with an alternative model based on deterministic queue dynamics, we estimate the benefit of considering queue stochasticity at 5% to 20%. Finally, comparisons with advanced heuristics aimed to imitate actual operating procedures suggest that the model can yield significant cost savings, estimated at 20% to 30%

Decomposition Algorithms for Analyzing Transient Phenomena in Multi-class Queueing Networks in Air Transportation

In a previous paper (Peterson, Bertsimas, and Odoni 1992), we studied the phenomenon of transient congestion in landings at a hub airport and developed a recursive approach for computing moments of queue lengths and waiting times. In this paper we extend our approach to a network, developing two approximations based on the method used for the single hub. We present computational results for a simple 2-hub network and indicate the usefulness of the approach in analyzing the interaction between hubs. Although our motivation is drawn from air transportation, our method is applicable to all multi-class queuing networks where service capacity at a station may be modeled as a Markov or semi-Markov process. Our method represents a new approach for analyzing transient congestion phenomena in such networks. Airport congestion and delay have grown significantly over the last decade. By 1986 ground delays at domestic airports averaged 2000 hours per day, the equivalent of grounding the entire fleet of Delta Airlines at that tillie (250 aircraft) for one day (Donoghue 1986). In 1990, 21 airports in the U.S. exceeded 20, 000 hours of delay, with 12 more projected to exceed this total by 1997 (National Transportation Research Board 1991). This amounts to *School of Public and Environmental Affairs, Indiana University, Bloomington, Indiana tSloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts ;Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, Massachusett

Carbon-Oxygen White Dwarfs Accreting CO-Rich Matter I: A Comparison Between Rotating and Non-Rotating Models

We investigate the lifting effect of rotation on the thermal evolution of CO WDs accreting CO-rich matter. We find that rotation induces the cooling of the accreting star so that the delivered gravitational energy causes a greater expansion with respect to the standard non-rotating case. The increase in the surface radius produces a decrease in the surface value of the critical angular velocity and, therefore, the accreting WD becomes gravitationally unbound (Roche instability). This occurrence is due to an increase in the total angular momentum of the accreting WD and depends critically on the amount of specific angular momentum deposited by the accreted matter. If the specific angular momentum of the accreted matter is equal to that of the outer layers of the accreting structure, the Roche instability occurs well before the accreting WD can attain the physical conditions for C-burning. If the values of both initial angular velocity and accretion rate are small, we find that the accreting WD undergoes a secular instability when its total mass approaches 1.4 Msun. At this stage, the ratio between the rotational and the gravitational binding energy of the WD becomes of the order of 0.1, so that the star must deform by adopting an elliptical shape. In this case, since the angular velocity of the WD is as large as 1 rad/s, the anisotropic mass distribution induces the loss of rotational energy and angular momentum via GWR. We find that, independent of the braking efficiency, the WD contracts and achieves the physical conditions suitable for explosive C-burning at the center so that a type Ia supernova event is produced.Comment: 39 pages, 22 eps-figures; accepted for publication in Astrophysical Journa